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https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
only convert pix_fmt when necessary
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a611cbb942
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@ -375,6 +375,8 @@ def main():
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best_object = object_processor.get_best(camera_name, label)
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best_frame = best_object.get('frame', np.zeros((720,1280,3), np.uint8))
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best_frame = cv2.cvtColor(best_frame, cv2.COLOR_YUV2BGR_I420)
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crop = bool(request.args.get('crop', 0, type=int))
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if crop:
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region = best_object.get('region', [0,0,300,300])
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@ -384,7 +386,6 @@ def main():
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width = int(height*best_frame.shape[1]/best_frame.shape[0])
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best_frame = cv2.resize(best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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ret, jpg = cv2.imencode('.jpg', best_frame)
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response = make_response(jpg.tobytes())
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response.headers['Content-Type'] = 'image/jpg'
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@ -411,11 +412,12 @@ def main():
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if frame is None:
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frame = np.zeros((720,1280,3), np.uint8)
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frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
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height = int(request.args.get('h', str(frame.shape[0])))
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width = int(height*frame.shape[1]/frame.shape[0])
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frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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ret, jpg = cv2.imencode('.jpg', frame)
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response = make_response(jpg.tobytes())
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@ -432,10 +434,10 @@ def main():
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if frame is None:
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frame = np.zeros((height,int(height*16/9),3), np.uint8)
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width = int(height*frame.shape[1]/frame.shape[0])
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frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
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width = int(height*frame.shape[1]/frame.shape[0])
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frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_LINEAR)
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frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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ret, jpg = cv2.imencode('.jpg', frame)
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yield (b'--frame\r\n'
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@ -260,7 +260,7 @@ class TrackedObjectProcessor(threading.Thread):
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def snapshot(camera, obj):
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if not 'frame' in obj:
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return
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best_frame = cv2.cvtColor(obj['frame'], cv2.COLOR_RGB2BGR)
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best_frame = cv2.cvtColor(obj['frame'], cv2.COLOR_YUV2BGR_I420)
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mqtt_config = self.camera_config[camera].get('mqtt', {'crop_to_region': False})
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if mqtt_config.get('crop_to_region'):
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region = obj['region']
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@ -70,6 +70,37 @@ def calculate_region(frame_shape, xmin, ymin, xmax, ymax, multiplier=2):
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return (x_offset, y_offset, x_offset+size, y_offset+size)
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def yuv_region_2_rgb(frame, region):
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height = frame.shape[0]//3*2
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width = frame.shape[1]
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# make sure the size is a multiple of 4
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size = (region[3] - region[1])//4*4
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x1 = region[0]
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y1 = region[1]
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uv_x1 = x1//2
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uv_y1 = y1//4
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uv_width = size//2
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uv_height = size//4
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u_y_start = height
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v_y_start = height + height//4
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two_x_offset = width//2
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yuv_cropped_frame = np.zeros((size+size//2, size), np.uint8)
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# y channel
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yuv_cropped_frame[0:size, 0:size] = frame[y1:y1+size, x1:x1+size]
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# u channel
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yuv_cropped_frame[size:size+uv_height, 0:uv_width] = frame[uv_y1+u_y_start:uv_y1+u_y_start+uv_height, uv_x1:uv_x1+uv_width]
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yuv_cropped_frame[size:size+uv_height, uv_width:size] = frame[uv_y1+u_y_start:uv_y1+u_y_start+uv_height, uv_x1+two_x_offset:uv_x1+two_x_offset+uv_width]
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# v channel
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yuv_cropped_frame[size+uv_height:size+uv_height*2, 0:uv_width] = frame[uv_y1+v_y_start:uv_y1+v_y_start+uv_height, uv_x1:uv_x1+uv_width]
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yuv_cropped_frame[size+uv_height:size+uv_height*2, uv_width:size] = frame[uv_y1+v_y_start:uv_y1+v_y_start+uv_height, uv_x1+two_x_offset:uv_x1+two_x_offset+uv_width]
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return cv2.cvtColor(yuv_cropped_frame, cv2.COLOR_YUV2RGB_I420)
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def intersection(box_a, box_b):
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return (
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max(box_a[0], box_b[0]),
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@ -14,7 +14,7 @@ import json
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import base64
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from typing import Dict, List
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from collections import defaultdict
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from frigate.util import draw_box_with_label, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond, listen, FrameManager, SharedMemoryFrameManager
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from frigate.util import draw_box_with_label, yuv_region_2_rgb, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond, listen, FrameManager, SharedMemoryFrameManager
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from frigate.objects import ObjectTracker
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from frigate.edgetpu import RemoteObjectDetector
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from frigate.motion import MotionDetector
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@ -88,7 +88,7 @@ def filtered(obj, objects_to_track, object_filters, mask=None):
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return False
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def create_tensor_input(frame, region):
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cropped_frame = frame[region[1]:region[3], region[0]:region[2]]
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cropped_frame = yuv_region_2_rgb(frame, region)
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# Resize to 300x300 if needed
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if cropped_frame.shape != (300, 300, 3):
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@ -304,13 +304,10 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape,
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regions = [calculate_region(frame_shape, a[0], a[1], a[2], a[3], 1.0)
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for a in combined_regions]
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if len(regions) > 0:
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rgb_frame = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
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# resize regions and detect
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detections = []
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for region in regions:
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detections.extend(detect(object_detector, rgb_frame, region, objects_to_track, object_filters, mask))
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detections.extend(detect(object_detector, frame, region, objects_to_track, object_filters, mask))
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#########
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# merge objects, check for clipped objects and look again up to 4 times
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@ -343,7 +340,7 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape,
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box[0], box[1],
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box[2], box[3])
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selected_objects.extend(detect(object_detector, rgb_frame, region, objects_to_track, object_filters, mask))
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selected_objects.extend(detect(object_detector, frame, region, objects_to_track, object_filters, mask))
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refining = True
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else:
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